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Industry:
Energy, Sustainability and Environment

AI-Driven Cloud Resource Allocation: Predictive Scaling & Cost Optimization Models

Expert Insights Delivered by :
Former Sr. Technologist
Intel Corporation

Category: 
Advanced
Insight Code: 
BNFT-0610-0133
Format: 
PDF / PPT / Excel
Deliverables: Transcript + Analyst Report + Infographic Pack

Discussion Guide

Transcript Summary

  • How do AI models predict workload spikes better than threshold-based rules?
  • What cost savings arise from spot instance bidding strategies?
  • How are predictive scaling algorithms tested for failure resilience?
  • What role do time-series databases play in training allocation models?
  • How do multi-cloud strategies complicate AI-driven resource optimization?
  • What FinOps dashboards provide actionable cost insights?
  • How are serverless and containerized workloads optimized differently?
  • What security risks emerge from autonomous scaling decisions?
  • How are energy costs factored into AI allocation models?
  • What benchmarks compare leading cloud cost optimization tools?
  • How are enterprises auditing AI allocation decisions for fairness?
  • What innovations will enable real-time global cloud arbitrage?

Transcript & Expert Details

Last Updated: September 2025
Expert's Experience: 22 Years
Relevant Experience: 12 Years
Call Duration: 122 Minutes
Base Year: 2024
Estimated Years: 2025 - 2030

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Singapore
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049422, Singapore
Jakarta

Revenue Tower, Scbd, Jakarta 12190, Indonesia
Mumbai
4th Floor, Pinnacle Business Park, Andheri East, Mumbai, 400093
Bangalore

Cinnabar Hills, Embassy Golf Links Business Park, Bengaluru, Karnataka 560071
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